An Optimization Model of Dynamic Allocation of Empty Railway Cars Based on Time-space Network
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摘要: 为合理配置空车资源,研究了路局(公司)管内空车调配的动态优化问题。构建区分时段长度的时空网络,以准确描述车站作业能力的变化。借鉴运输问题(TP)的基本思想,通过引入空车供需约束,将动态空车调配问题转化为基于时空网络的多商品网络流问题。结合空车调配的特点,设置2组整数决策变量,将分界站排空与局(公司)管内配空分开考虑。设置0-1辅助变量构建车种代用约束。在此基础上,以总费用最小为目标,构建了空车调配动态优化的混合整数规划模型。以中国铁路昆明局集团有限公司管内空车调配为例,验证了模型的可行性与有效性。算例结果表明,与静态空车调配方法相比,构建的动态空车调配模型不仅降低了空车调配总成本,而且调配方案更加贴合实际。与现有动态空车调配方法相比,通过改变时空网络中时段的划分方式,降低了模型求解的复杂度,构建的模型在获取空车调配方案的同时能够更加直观的看出空车在不同时间的作业状态。Abstract: The paper studies the dynamic optimization of the empty car distribution within the railway administration (or company)to reasonably allocate empty cars. The time-space network with different periods is constructed to describe the changes in work capacities of railway stations. By referring to transportation problems, dynamic empty-car distribution is transformed into the multi-commodity network flow based on the time-space network by increasing the supply and demand constraints. Combining the characteristics of empty car distribution, the paper develops two sets of integer decision variables and considers discharging and assigning empty cars separately. 0-1 auxiliary variables are set to construct substitution constraints of car types. On this basis, a mixed-integer programming model for the dynamic optimization of empty-car distribution is constructed to minimize the total cost. The feasibility and effectiveness of the model are verified by taking empty-car distribution in Kunming railway administration as a case study. The results show that dynamic empty-car distribution is superior to static empty-car distribution in reducing the total cost and fitting the actual process. The complexity of solving the model is reduced by improving the time-space network compared with the existing methods of dynamic empty-car distribution. The model can obtain the scheme of empty-car distribution and check the operation status of empty cars at different times intuitively.
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表 1 车站装车比重排序表
Table 1. List of loading proportions at stations
排序 单位名 装车比重/% 收人比重/% 1 王家营 10.141 7 13.212 8 2 读书铺 8.323 1 10.189 2 3 中谊村 07.906 2 07.504 2 4 昆明东 04.500 3 06.188 9 5 白塔村 04.462 2 06.509 7 6 红果 04.014 8 01.832 8 7 曲靖 03.803 3 04.188 6 8 柏果 03.650 0 02.317 4 9 宣威 03.245 9 01.709 2 10 盘关 03.057 3 00.320 4 11 平田 02.650 6 02.026 4 12 金马村 02.481 0 03.342 3 13 威舍 02.401 6 01.265 5 14 火铺 01.928 6 01.557 4 15 月亮田 01.818 0 01.933 3 16 大理东 01.743 4 05.253 4 17 禄丰 01.662 1 01.356 3 18 昆明西 01.654 7 01.915 6 19 陆良 01.653 8 01.655 6 20 珠江源 01.567 0 01.263 8 表 2 空车需求站请求空车情况
Table 2. Requested conditions of stations demanding for empty cars
空车需求站 空车需求情况 货物种类 装运时间 柏果 罐车20车 石油 时段7 威舍 敞车30车 煤炭 时段8 陆良 敞车10车 煤炭 时段4 中谊村 棚车50车或敞车52车 粮食 时段5 大理东 敞车10车 煤炭 时段9 分界站宣威 棚车60车 时段8 表 3 空车供给站有效空车数
Table 3. Effective number of empty cars of supply stations
空车供给站 有效空车数 卸空时段 红果 敞车80车、罐车30车 时段2 昆明东 敞车100车、棚车100车 时段2 读书铺 敞车50车、棚车60车 时段2 禄丰 敞车20车 时段5 表 4 列车编组计划
Table 4. Formation of freight trains
发站 到站 列车种类 定期车次 昆明东 宣威 摘挂 22 608 宣威 曲靖 直通 22 617 曲靖 柏果 摘挂 45 307 红果 柏果 区段 45 305 曲靖 威舍 摘挂 45 316 昆明东 威舍 摘挂 37 008 昆明东 中谊村 摘挂 46 212 读书铺 禄丰 摘挂 51 781 读书铺 大理东 空车直达 51 981 禄丰 大理东 直通 51 987 读书铺 昆明东 区段 46 105 昆明东 宣威 直通 22 617 表 5 模型求解结果
Table 5. Model solutions
供给节点 需求节点 空车数量/车 调配方案 车种 红果 柏果 20 C2-C3-C4-C5-C6-B7 罐车 红果 威舍 30 C2-C3-C4-C5-C6-G7-G8 敞车 昆明东 陆良 10 E2-H4 敞车 昆明东 中谊村 52 E2-I3-I4-I5 棚车 禄丰 大理东 10 J5-K8-K9 敞车 昆明东 宣威 48 E2-A4-A5-A6-A7-A8-A9 棚车 读书铺 12 F2-F3-F4-F5-F6-E7-A9 棚车 表 6 不同策略下调配结果对比
Table 6. Result comparison under different strategies
策略 供给节点 需求节点 空车数量/车 车种 总成本/元 静态多阶段优化 阶段1 昆明东 陆良 10 敞车 100 450 读书铺 中谊村 52 棚车 红果 柏果 20 罐车 阶段2 红果 威舍 30 敞车 禄丰 大理东 10 敞车 昆明东 宣威 60 棚车 红果 柏果 20 罐车 动态优化 红果 威舍 30 敞车 99 560 昆明东 陆良 10 敞车 昆明东 中谊村 52 棚车 禄丰 大理东 10 敞车 昆明东 宣威 48 棚车 读书铺 12 棚车 -
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